The C4 Rice Consortium coordinates efforts from labs all over the world trying to isolate the genes responsible in C4 plants and apply them in C3 plants. If successful, yields in wheat and rice are expected to be 50% higher than present. An impressive result seen as vital for future food security. The consortium is led by Jane Langdale at the University of Oxford and funded by the Bill & Melinda Gates Foundation.

With a rapidly growing population, improving the yield of global food staples such as rice has become an urgent focus for plant scientists.

In a recent study published on Plant Physiology, scientists have discovered they can improve rice productivity by selecting rice varieties that are better at capturing sunlight to produce grains instead of reflecting it as heat.

“We studied hundreds of plants from five rice cultivars and found that there is variation between these varieties in relation to the quantity of light they use for growth or dissipate as heat. Some of them are capable of converting more sunlight into chemical energy, producing greater leaf area over time,” said lead researcher, Dr Katherine Meacham.

When leaves intercept sunlight, this sunlight is either; 1) absorbed by the leaf and converted via the process of photosynthesis into the plants own components; leaves, grains, roots, etc. 2) dissipated as heat as an strategy to protect the proteins of the plant from sun damage (photo-protection) or, 3) re-emitted as fluorescent light. In this study, the researchers measured fluorescence to infer the quantity of energy that is either converted into food or dissipated as heat.

“What is new about our research is that scientists had previously thought there was not much variation in how efficiently leaves could absorb and use light, and the reason for this is that they were not considering the full picture and measuring the plants throughout the entire day under natural illumination. We revealed that there are considerable differences between the five rice cultivars under moderate light and that means that there is room for selecting the most efficient plants,” said Professor Furbank.

“We found that there is room for improvement in some cultivars that can result in more photosynthesis without risking the plant’s protection strategies against sunlight damage.

The scientists measured fluorescence by clipping light receptors on leaves throughout a whole day to get a full picture of how the plant uses sunlight.

Traditional breeding for photosynthetic traits has not been a common strategy in any major cereal crop, in part due to the difficulty in measuring photosynthesis in thousands of plants. However, rapid screening tools are now available to study the interaction between the genes and the way they interact with the environment.

“Using unique facilities at the Australian Plant Phenomics Facility’s High Resolution Plant Phenomics Centre we were able to follow chlorophyll fluorescence in rice canopies throughout the entire day under natural illumination. This gave us completely different results when compared to the usual 30 min measurement of leaf level light use efficiency. By combining this with digital biomass analysis using PlantScan, we could link light use efficiency with growth, revealing genetic variation in rice varieties not previously detected,” said Professor Furbank.

“Our next step is to find varieties with superior photo-protection. We can directly use these for breeding and find the genes responsible. We have the capacity to screen many thousands of rice varieties for which we have gene sequence through the International Rice Research Institute,” said Dr Meacham.

With indoor-vertical farming on the rise, lettuce production can be customised more than ever, by choosing the right varieties, temperature, lighting and nutrient supply to produce the leaves consumers want. Achieving this goal requires optimisation of numerous components and a recent collaborative study between the USA and Australia, published in Frontiers in Plant Science, has proven optical sensors can be used to evaluate lettuce growth, color and health non-destructively.

The research team, Ivan Simko and Ryan Hayes from the US Department of Agriculture and Robert Furbank from the ARC Centre of Excellence for Translational Photosynthesis and formerly Australian Plant Phenomics Facility – High Resolution Plant Phenomics Centre, designed the study to test the feasibility of using optical sensors for physiological evaluation of lettuce plants in early stages of their development. The method developed can help in breeding programs and optimising farming practices to meet the requirements of an increasingly demanding market.

Read the full study, Non-destructive phenotyping of lettuce plants in early stages of development with optical sensors, published in Frontiers in Plant Science,here.

Or read the abstract here:

Abstract

Rapid development of plants is important for the production of ‘baby-leaf’ lettuce that is harvested when plants reach the four- to eight-leaf stage of growth. However, environmental factors, such as high or low temperature, or elevated concentrations of salt, inhibit lettuce growth. Therefore, non-destructive evaluations of plants can provide valuable information to breeders and growers. The objective of the present study was to test the feasibility of using non-destructive phenotyping with optical sensors for the evaluations of lettuce plants in early stages of development. We performed the series of experiments to determine if hyperspectral imaging and chlorophyll fluorescence imaging can determine phenotypic changes manifested on lettuce plants subjected to the extreme temperature and salinity stress treatments. Our results indicate that top view optical sensors alone can accurately determine plant size to approximately 7 g fresh weight.

Comparison of the size and the colour of plants cultivated at optimal (OPT), low (COLD) and high (HOT) temperatures (experiment 3). Plants were initially grown at OPT for 10 days and the either continuously kept in OPT or transferred to COLD or HOT for 8 days. Sides of the square pots are 68mm long.

Hyperspectral imaging analysis was able to detect changes in the total chlorophyll (RCC) and anthocyanin (RAC) content, while chlorophyll fluorescence imaging revealed photoinhibition and reduction of plant growth caused by the extreme growing temperatures (3 and 39°C) and salinity (100 mM NaCl). Though no significant correlation was found between Fv/Fm and decrease in plant growth due to stress when comparisons were made across multiple accessions, our results indicate that lettuce plants have a high adaptability to both low (3°C) and high (39°C) temperatures, with no permanent damage to photosynthetic apparatus and fast recovery of plants after moving them to the optimal (21°C) temperature. We have also detected a strong relationship between visual rating of the green- and red-leaf color intensity and RCC and RAC, respectively. Differences in RAC among accessions suggest that the selection for intense red color may be easier to perform at somewhat lower than the optimal temperature.

Genomic position of the quantitative trail locus (QTL) for light green colour (qLG4) on linkage group 4. Visual rating of the green colour intensity was performed on adult plants in field, while the relative chlorophyll content (RCC) was determined from hyperspectral reflectance measured on cotyledons of seedlings cultivated in plastic boxes (experiment 7). The orange line parallel with the linkage map shows the significance threshold (a = 0.05). The allele for light green colour and low RCC originates from cv. La Brilliante. Detailed description of the linkage map for this population and its construction was published previously (Hayes et al., 2014; Simko et al., 2015b). Distance in cM is shown on the right site of the linkage map. LOD, logarithm of odds.

This study serves as a proof of concept that optical sensors can be successfully used as tools for breeders when evaluating young lettuce plants. Moreover, we were able to identify the locus for light green leaf color (qLG4), and position this locus on the molecular linkage map of lettuce, which shows that these techniques have sufficient resolution to be used in a genetic context in lettuce.

A method for cost-effective, reliable and scalable airborne thermography has been developed, resolving a number of challenges surrounding accurate high-throughput phenotyping of canopy temperature (CT) in the field, such as weather changes and their influence on more time consuming measurement methods. Utilising a manned helicopter carrying a radiometrically-calibrated thermal camera, thermal image data is captured in seconds and processed within minutes using custom-developed software; an invaluable advantage for large forward genetic studies or plant breeding programs.

The method and research results, by a collaboration between CSIRO Agriculture and Food, the Australian Plant Phenomics Facility – High Resolution Plant Phenomics Centre, CSIRO Information Management and Technology, and the ARC Centre of Excellence for Translational Photosynthesis were published recently in Frontiers in Plant Science.

Read the full study, “Methodology for high-throughput field phenotyping of canopy temperature using airborne thermography”,hereor the abstract below.

Airborne thermography image acquisition and processing pipeline. Total time to acquire and process images for an experiment comprising 1,000 plots of size 2 x 6 m is ca. 25 min. (A) Image acquisition with helicopter. The images are recorded on a laptop and the passenger, left, provides real time assessment of the images and feedback to the pilot. This step takes < 10 s for an experiment comprising 1,000 plots of size 2 x 6 m. (B) Screenshot of custom-developed software called ChopIt. ChopIt is used for plot segmentation and extraction of CT from each individual plot for statistical analysis. This step takes ca. 20 min for an experiment comprising 1,000 plots of size 2 x 6 m.

Lower canopy temperature (CT), resulting from increased stomatal conductance, has been associated with increased yield in wheat. Historically, CT has been measured with hand-held infrared thermometers. Using the hand-held CT method on large field trials is problematic, mostly because measurements are confounded by temporal weather changes during the time required to measure all plots. The hand-held CT method is laborious and yet the resulting heritability low, thereby reducing confidence in selection in large scale breeding endeavors. We have developed a reliable and scalable crop phenotyping method for assessing CT in large field experiments. The method involves airborne thermography from a manned helicopter using a radiometrically-calibrated thermal camera. Thermal image data is acquired from large experiments in the order of seconds, thereby enabling simultaneous measurement of CT on potentially 1000s of plots. Effects of temporal weather variation when phenotyping large experiments using hand-held infrared thermometers are therefore reduced. The method is designed for cost-effective and large-scale use by the non-technical user and includes custom-developed software for data processing to obtain CT data on a single-plot basis for analysis. Broad-sense heritability was routinely >0.50, and as high as 0.79, for airborne thermography CT measured near anthesis on a wheat experiment comprising 768 plots of size 2 × 6 m. Image analysis based on the frequency distribution of temperature pixels to remove the possible influence of background soil did not improve broad-sense heritability. Total image acquisition and processing time was ca. 25 min and required only one person (excluding the helicopter pilot). The results indicate the potential to phenotype CT on large populations in genetics studies or for selection within a plant breeding program.